【摘要】：道路交叉口排隊長度的探測能夠對交通擁堵形成有效的監(jiān)測與預防,對緩解路網壓力、促進城市交通健康發(fā)展有著積極的作用。浮動車運行時所產生的軌跡數(shù)據(jù)(簡稱浮動車GPS數(shù)據(jù))是一種典型的移動式數(shù)據(jù),針對這些數(shù)據(jù)進行分析與挖掘,從而實現(xiàn)排隊長度的探測是當下的研究熱點。然而,現(xiàn)有研究往往存在工程應用條件嚴苛和參數(shù)設定只能針對具體道路交叉口的適用性問題,同時缺乏對數(shù)據(jù)樣本容量的相關研究。針對這些問題,本文以深圳市大規(guī)模浮動車GPS數(shù)據(jù)為基礎,提出一種基于空間分布模式的道路交叉口排隊長度探測算法,并研究相應的最佳樣本容量。論文首先對數(shù)據(jù)進行預處理,綜合道路中介中心性和浮動車流量得到不同屬性的道路集合,在分析原始數(shù)據(jù)采樣間隔的分布后選取了統(tǒng)一的軌跡采樣間隔;然后根據(jù)排隊形成的機理,提取排隊車輛的軌跡點特征,通過引入空間分布模式的分析方法,定量地獲得了道路上軌跡點的空間點格局,并結合提取的特征實現(xiàn)了排隊長度的探測;最后,分析浮動車GPS樣本容量對探測結果和算法效率的影響,并利用核密度估計原理得到不同樣本容量下的軌跡點在道路上的密度分布曲線,通過定量地度量曲線穩(wěn)定性,確定最佳樣本容量。實驗結果表明,所提算法在保證高精度的前提下具有很強的適用性,可用于多種類型道路交叉口的排隊長度探測。此外,本文確定的最佳樣本容量具有很高的正確性,同時得出了屬性相似道路形成的道路交叉口,排隊長度探測的最佳樣本容量具有一致性的結論。本文以浮動車GPS數(shù)據(jù)為研究對象,提出了具有強適應性的排隊長度探測算法,并確定了相應的最佳樣本容量,為大規(guī)模城市道路交叉口的車輛排隊長度探測提供了新的方法與思路。
[Abstract]:The detection of queue length at intersections can effectively monitor and prevent traffic congestion, relieve road network pressure and promote the healthy development of urban traffic. The track data (GPS data for short) generated by floating vehicle is a kind of typical mobile data. It is a hot research topic to analyze and mine these data and realize the detection of queue length. However, the existing research often has the problem that the engineering application conditions are strict and the parameter setting can only be applied to the specific road intersection, and there is a lack of relevant research on the data sample size at the same time. In order to solve these problems, based on the GPS data of large-scale floating vehicles in Shenzhen City, this paper presents an algorithm of queue length detection for road intersections based on spatial distribution pattern, and studies the corresponding optimal sample size. Firstly, the data are preprocessed, and the road sets with different attributes are obtained by synthesizing the road intermediary centrality and floating vehicle flow. After analyzing the distribution of the sampling interval of the original data, the uniform track sampling interval is selected. Then according to the mechanism of queue formation, the characteristics of trajectory points of queued vehicles are extracted. By introducing the analysis method of spatial distribution mode, the spatial point pattern of trajectory points on the road is obtained quantitatively. Finally, the influence of the GPS sample size on the detection results and the efficiency of the algorithm is analyzed. Based on the kernel density estimation principle, the density distribution curves of trajectory points on the road under different sample sizes are obtained, and the optimal sample size is determined by quantitatively measuring the stability of the curves. The experimental results show that the proposed algorithm has strong applicability on the premise of high accuracy and can be used to detect the queue length of many kinds of road intersections. In addition, the optimal sample size determined in this paper has a high accuracy, and the conclusion that the optimal sample size of queue length detection is consistent is obtained for the road intersection with similar attributes. In this paper, based on the GPS data of floating vehicle, a strong adaptive queue length detection algorithm is proposed, and the corresponding optimal sample size is determined. It provides a new method and train of thought for vehicle queue length detection at large-scale urban road intersections.
【學位授予單位】：深圳大學
【學位級別】：碩士
【學位授予年份】：2017
【分類號】：U491

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1 齊瑋;;略議道路交叉口的建筑藝術造型[J];華中建筑;1991年01期

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本文編號：2140824